Methods and systems for forming images of eye features using a non-imaging, scanning-MEMS-based eye-tracking system

ABSTRACT

Aspects of the present disclosure describe systems, methods, and structures that provide eye-tracking by 1) steering a beam of light through the effect of a microelectromechanical system (MEMS) onto a surface of the eye and 2) detecting light reflected from features of the eye including corneal surface, pupil, iris—among others. Positional/geometric/feature/structural information pertaining to the eye is determined from timing information associated with the reflected light.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority of U.S. Provisional Patent ApplicationSer. No. 63/150,312, filed Feb. 17, 2021, which is incorporated hereinby reference. It also includes concepts disclosed in United StatesPatent Publication Nos. 2019/0204912 published 4 Jul. 2019, 2016/0166146published 16 Jun. 2016, 2017/0276934 published 28 Sep. 2017, and2021/0124416 published 29 Apr. 2021, each of which is incorporatedherein by reference.

TECHNICAL FIELD

This disclosure relates generally to human—computer interfaces and morespecifically to eye-tracking systems, methods and structures thatadvantageously provide real-time measurements of eye-tracking and eyefixations, as well as imaging of features of an eye.

BACKGROUND

Much information about a user can be derived from knowledge of theuser's gaze direction, as well as the shape, location, orientationand/or movement of particular features of one or both of the user'seyes.

Historically, such information has been obtained using eye-trackingsystems that rely on imaging systems (e.g., cameras, focal-plane arrays(FPA), etc.) for forming an image of one or both eyes and complex imageprocessing to interpret such images. Unfortunately, eye-tracking systemsthat employ imaging systems are notoriously slow (high-latency),expensive, bulky and require considerable processing power. As a result,they are not well suited for use in many applications.

Given such applicability and importance, improved eye-tracking systems,methods and/or structures that can form images of an eye or one or moreof its features, without the use of a conventional imaging system andassociated image processing would represent a welcome addition to theart.

SUMMARY

The present disclosure is directed to the formation of an image of aportion of an eye based on information derived using a non-imaging,scanning-MEMS-based eye tracking system. Methods and structuresaccording to aspects of the present disclosure advantageously facilitatethe rapid forming of an image of an eye, or features thereof, withoutthe need for a conventional imaging system, such as a camera orfocal-plane array, thereby enabling development of gaze-directionestimations and/or ophthalmological measurement instruments fordetermining geometric and/or other eye features exhibiting a precisionand reproducibility unknown in the art. Such determinationsadvantageously include shape(s), geometry(ies), and motion of eyefeature(s) including the cornea, pupil, iris, sclera, eyelid, etc., aswell as their respective interfaces.

Systems, methods, and structures providing eye-tracking according toaspects of the present disclosure advantageously facilitate themeasurement of subject eye-movements during—for example—psychological orconsumer behavior studies and evaluations, neurological examinations,and the like.

In a broad context, systems, methods, and structures according to thepresent disclosure provide eye-tracking and/or feature imaging bysteering a beam of light through the effect of a two-axis, resonantmicroelectromechanical system (MEMS) beam scanner onto a scan region ofthe face including the eye. Structures within the scan region, such ascorneal surface, pupil, iris, sclera, and/or eyelid are thentracked/imaged by detecting reflections (or the absence thereof) oflight from the scan region at one or more discrete detectors.

According to aspects of the present disclosure, a tracked glint (i.e.,short flash of reflected light) is detected as large amplitude pulse ofnarrow width whereas a tracked pupil is detected as an absence ofreflected light in a region of a scanned pattern. In some embodiments,one or more discrete detectors are advantageously selected to use anegative threshold for pupil tracking and/or a positive threshold forglint tracking, thereby enabling the discrimination between glintfeatures and pupil features. By judicious selection of the detectionthreshold, discrimination between regions/features of the eye havingdifferent reflectivities can be performed.

Advantageously, a projected scan pattern (Lissajous) is employed thatproduces a superior spatiotemporal scanning density over the scanregion. In some embodiments, the projected pattern is generated suchthat it precesses, thereby further improving the spatiotemporal scanningdensity.

Of further advantage, when sufficient number of pulses aredetected/collected by the multiple detectors, a contour map of theglint(s) and location(s) of eye features may be obtained.

Still further, by performing multiple scans of the eye with differentoptical powers and/or different detection thresholds, contour plots ofthe eye can be generated and used to derive a reflected-intensity maprepresentation of the eye.

In some embodiments, a reflected-intensity map may be obtained bydirectly sampling the magnitude of the reflected signal from the scannedregion by way of an analog to digital converter and mapping the positionof the scanned beam to a memory address in a frame buffer and settingthe value of the memory address to the measured intensity.

An embodiment in accordance with the present disclosure is an apparatuscomprising: a first microelectromechanical system (MEMS) scanner forsteering a first input light signal in a two-dimensional pattern over ascan region, wherein the first MEMS scanner has a first scanning axischaracterized by a first resonant frequency and a second scanning axischaracterized by a second resonant frequency; a detector configurationthat is non-imaging and includes at least one discrete detector, whereinthe detector configuration is configured to provide a first detectorsignal based on reflected light from the scan region, the reflectedlight comprising at least a portion of the input light signal; acomparator configured to provide a first comparator signal based on afirst comparison of the first detector signal and a first threshold; anda processor configured to estimate the position of the MEMS scanner andgenerate a first contour plot based on a spatiotemporal correlation ofthe first comparator signal and the estimated position of the MEMSscanner over the first time period.

Another embodiment in accordance with the present disclosure is a methodcomprising: scanning a first input light signal in a two-dimensionalscan pattern over a scan region through the effect of amicroelectromechanical system (MEMS) scanner that has a first scanningaxis characterized by a first resonant frequency and a second scanningaxis characterized by a second resonant frequency, wherein the lightsignal is scanned by driving the first axis with a first periodic signalhaving a first drive frequency and driving the second axis with a secondperiodic signal having a second drive frequency; providing a firstdetector signal based on reflected light from the scan region at adetector configuration that is non-imaging and includes at least onediscrete detector, wherein the reflected light comprises at least aportion of the input light signal; generating a first comparator signalbased on a first comparison of the first detector signal and a firstthreshold; and generating a first contour plot based on a spatiotemporalcorrelation between the first comparator signal and an estimate of theposition of the MEMS scanner over a first time period.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a schematic block diagram showing an illustrative eyetracking system according to aspects of the present disclosure.

FIG. 2A is a schematic diagram depicting an illustrative geometricarrangement for an eye-tracking system in accordance with the presentdisclosure.

FIG. 2B shows a schematic diagram depicting an exemplary scan region ofa subject eye according to aspects of the present disclosure.

FIGS. 3A-B shows examples of precessing Lissajous curve patternsgenerated by driving a two-axis, resonant MEMS scanner with drivesignals having different drive-frequency ratios according to aspects ofthe present disclosure.

FIG. 4 depicts a plot of scan density of a scan pattern versus thenumber of drive-signal cycles, k, for two drive signals having differentsets of drive frequencies.

FIG. 5 depicts operations of a method suitable for identifying athresholded feature according to aspects of the present disclosure.

FIG. 6A depicts a plot of output signal 130 over the measured half-scanperiod of scan pattern 302.

FIG. 6B depicts a two-dimensional map of the output signal of comparator132.

FIG. 6C depicts a reconstructed pupil signal in accordance with method500.

FIG. 7 depicts operations of a method suitable for forming a multi-levelreflected-intensity map of an eye in accordance with the presentdisclosure.

FIG. 8A depicts a series of contour plots in accordance with the presentdisclosure.

FIG. 8B depicts a contour map in accordance with the present disclosure.

FIG. 8C depicts an image of an eye derived by interpolating a contourmap in accordance with the present disclosure.

FIG. 9 depicts image plots of a portion of a face reconstructed usingdifferent numbers of bits of information in accordance with the presentdisclosure.

DETAILED DESCRIPTION

The following merely illustrates the principles of the disclosure. Itwill thus be appreciated that those skilled in the art will be able todevise various arrangements which, although not explicitly described orshown herein, embody the principles of the disclosure and are includedwithin its spirit and scope.

Furthermore, all examples and conditional language recited herein areprincipally intended expressly to be only for pedagogical purposes toaid the reader in understanding the principles of the disclosure and theconcepts contributed by the inventor(s) to furthering the art, and areto be construed as being without limitation to such specifically recitedexamples and conditions.

Moreover, all statements herein reciting principles, aspects, andembodiments of the disclosure, as well as specific examples thereof, areintended to encompass both structural and functional equivalentsthereof. Additionally, it is intended that such equivalents include bothcurrently known equivalents as well as equivalents developed in thefuture, i.e., any elements developed that perform the same function,regardless of structure.

Thus, for example, it will be appreciated by those skilled in the artthat any block diagrams herein represent conceptual views ofillustrative circuitry embodying the principles of the disclosure.Similarly, it will be appreciated that any flow charts, flow diagrams,state transition diagrams, pseudo code, and the like represent variousprocesses which may be substantially represented in computer readablemedium and so executed by a computer or processor, whether or not suchcomputer or processor is explicitly shown.

The functions of the various elements shown in the Drawing, includingany functional blocks that may be labeled as “processors”, may beprovided through the use of dedicated hardware as well as hardwarecapable of executing software in association with appropriate software.When provided by a processor, the functions may be provided by a singlededicated processor, by a single shared processor, or by a plurality ofindividual processors, some of which may be shared. Moreover, explicituse of the term “processor” or “controller” should not be construed torefer exclusively to hardware capable of executing software, and mayimplicitly include, without limitation, digital signal processor (DSP)hardware, network processor, application specific integrated circuit(ASIC), field programmable gate array (FPGA), read-only memory (ROM) forstoring software, random access memory (RAM), and non-volatile storage.Other hardware, conventional and/or custom, may also be included.

Software modules, or simply modules which are implied to be software,may be represented herein as any combination of flowchart elements orother elements indicating performance of process steps and/or textualdescription. Such modules may be executed by hardware that is expresslyor implicitly shown.

Unless otherwise explicitly specified herein, the figures comprising thedrawing are not drawn to scale.

As will become apparent to those skilled in the art, systems, methods,and structures according to aspects of the present disclosureadvantageously extend the capabilities of eye tracking systems disclosedin U.S. Patent Publication Nos. US2016/0166146 (hereinafter referred toas the '146 publication), US2019/0204912 (hereinafter referred to as“the '912 publication”), and US2021/0124416 (hereinafter referred to as“the '416 publication”) which disclosed scanning microelectromechanicalsystems that determine the position of an eye by directing a beam oflight towards the eye and determining the unique angle at which the beamreflects off the cornea of the eye to determine the direction of thegaze of the user. Systems in accordance with the '146, '912, and '416publications enable eye tracking that can be faster, lower power, moreprecise, more compact, and lower cost than prior-art video-basedsystems.

FIG. 1 shows a schematic block diagram illustrating an eye trackingsystem according to aspects of the present disclosure. As will beapparent to those skilled in the art by inspection of this figure andthe following discussions, such illustrative systems constructedaccording to aspects of the present disclosure advantageously exhibitsubstantial improvements in size, cost, power consumption, bandwidth andprecision as compared with prior art eye-tracking systems.

In broad terms, system 100 includes a transmit module that emits one ormore beams of light at controlled angle(s) toward a scan region on theeye being tracked. Through the effect of one or more MEMS scanningmicromirrors included in the transmit module, each beam of light isscanned over time, in any pattern on the scan region, but preferably ina Lissajous figure.

The beam of light interacts with one or many object(s) of interest orfeature(s) in the environment. Such an object or feature can especiallyinclude features such as pupil, iris, cornea, sclera, eyelid, and thelike. The object(s) of interest or feature(s) of the environment maychange position and/or orientation, or other features, over time. Theinteraction of the beam of light with the object of interest or featurein the environment may include reflection, retroreflection,transmission, blocking, absorption, polarization change, or any otherinteraction that alters one or more properties of the beam of lightafter the interaction.

One or more photodetectors (“detector(s)”) measures reflections of thebeam of light received from the scan region over time, where thereflections (or lack thereof) arise from the interaction of the beam oflight with the one or more objects of interest or features in the scanregion.

A detector may include additional electronic circuits to aid in itsoperations. A detector may be positioned in a package with a scanner.The measurement of the optical signal(s) from the beam(s) of lightcontains information such as optical intensity, timing information, timeof flight, pulse width, modulation frequency, or any other property ofthe beam(s) of light. The detectors may change their gain, threshold,dynamic range, or any other property related to measuring the beam(s) oflight over time. The detector(s) may be powered off or put into areduced power state for a period of time. Thresholded signals frommultiple detectors can be combined using logical operations; OR, NOR,AND, NAND, etc. operations with electronic circuits. Similarly, analogintensity signals from multiple detectors may be combined through analogsumming, difference or other arithmetic operations using analog meanssuch as through the use of operational amplifiers.

In some embodiments, the beam(s) of light are optically modulated toimprove detectability. In some embodiments, the modulation signalcontains digital information. In some embodiments, the opticalmodulation signal is adjusted over time to, for example, improvedetectability. Furthermore, in some embodiments, another aspect of thebeam(s) of light is adjusted over time, such optical power, patterntype, size, position, rate, and the like. In some cases, the opticalpower is reduced to zero and/or the MEMS scanning micromirror module ispowered off or put into a reduced power state for some period of time.

The detector(s) may use demodulation to detect a reflection of anoptically modulated signal. The demodulation frequency or frequencyrange may be changed over time. The detectors may decode digitalinformation carried in the modulated beam(s) of light.

The signals produced by the detector(s) and associated electroniccircuits are provided to a processor or microprocessor for use insoftware. An analog to digital converter, or a comparator, or any otherprocess that converts electronic signals to digital information may beused to provide the processor or microprocessor with the opticalinformation.

With specific reference to FIG. 1 , illustrative system 100 includes oneor more transmit module(s) 102, detect module(s) 104 (that may includemultiple individual detectors)—not specifically shown, and processor(s)106. Note that for simplicity in the drawing, only single module(s) areshown in this illustrative figure. Those skilled in the art will ofcourse appreciate that the number(s) and function(s) of the module(s)are not fixed, and instead may include a plurality of same. Stillfurther, their respective position(s) may likewise be varied from thoseillustratively shown including spaced-apart relative to one anotherand/or arranged in a pre-determined or no particular arrangementaround—for example—eyeglass frames or goggles or shield or othermechanical support.

Transmit module 102 and detect module 104 are illustratively shownarranged on a rigid support in a fixed orientation relative to an eye120 of a test subject. As we shall show and describe, system 100 enablestracking of a surface feature (e.g., cornea 124, pupil, iris, sclera,and the like—not specifically shown) within a two-dimensional region ofan eye during typical test-subject behavior (e.g., reading, viewing acomputer screen, watching television, monitoring a scene, shopping,other consumer activities, responding to stimulus, etc.), and estimatingand/or determining the corneal vector of the eye based on the locationof the surface feature (and other characteristics). In addition, system100 can be used to detect other eye features and/or user behavior, suchas an eyelid, blink, blink rate, saccade activity, eyelid droop, and thelike, that can provide insight into the physical/emotional state of theuser.

For the purposes of this Specification, including the appended claims,the “corneal vector” or “gaze vector” of an eye is defined as the gazedirection of the eye. As may be readily appreciated by those skilled inthe art, we note that the optical axis of an eye is not the same as avisual axis. More specifically, the optical axis may be substantiallyaligned—for illustrative example—with an optical centerline of the eyewhile the visual axis is more substantially aligned with a visual acuitylocation of the eye, namely the fovea centralis. The fovea isresponsible for sharp central vision, which is necessary in humans foractivities where visual detail is of primary importance, such as readingand driving. Accordingly, a gaze vector is preferably indicated by avector extending outward along the visual axis. As used herein and aswill be readily understood by those skilled in the art, “gaze” suggestslooking at something—especially that which produces admiration,curiosity or interest—among other possibilities.

Transmit module 102 is a sub-system for providing input signal 116 andscanning it in two-dimensions over a scan region 122 of eye 120.Transmit module 102 includes at least one light source for generatinglight and at least one MEMS scanner for steering the light in twodimensions. Typically, collimating optics are also included in atransmit module or operatively coupled with it such that input signal116 is received as a substantially collimated light signal at eye 120.Exemplary transmit modules are described in detail in the '146, '912,and '416 publications; however, it should be noted that transmit modulesin accordance with the present disclosure are not limited to thosedisclosed in the '146, '912, and '416 publications.

Furthermore, in some embodiments, the optical path of input signal isfolded and/or interacts with an optical element (e.g., a collimatinglens, partially collimating lens, off-axis parabola, mirror,metasurface, etc.) prior to the input signal being received at eye 120,as described in U.S. patent application Ser. No. 16/232,410, filed Dec.26, 2018, which is incorporated herein by reference.

Detect module 104 is a sub-system for receiving light reflected fromscan region 122, providing an electrical signal based on the intensityof the reflected light, and detecting—among other possible things—one ormore maxima in the electrical signal.

Exemplary detect modules are described in detail in the '146, '912, and'416 publications; however, it should be noted that detect modules inaccordance with the present disclosure are not limited to thosedisclosed in the '146, '912, and '416 publications.

As noted previously, while only a single detect module is shown in theillustrative FIG. 1 , those skilled in the art will appreciate that morethan one detect module may be employed—each having one or moreindividual detectors included therein. As will become furtherappreciated, such configurations including multiple detect modulesand/or multiple detectors therein, provide additional data/informationaccording to aspects of the present disclosure. We note at this pointthat the above discussion generally describes the detection of maxima.Advantageously, minima are also possible to detect in the case of thepupil. As we shall further show and describe, systems, methods andstructures according to aspects of the present disclosure may detectother optical power levels that can be used to, for example, identifyedges of features, feature contours, and the like, which can be moredifficult to identify. In such an application, we may advantageouslyedge outlines of features and fit—for example—ellipses to facilitatetheir identification.

Processor 106 may be a conventional digital processor and controller(e.g., a microcontroller, microcomputer, etc.) operative for controllingtransmit module 102, establishing system timing, and estimating thetwo-dimensional location of cornea 124 (for example) within scan region122. In the depicted example, processor 106 includes conventionalcomparator 132 and communicates with transmit module 102 and detectmodule(s) 104 via wired connections (not shown) to transmit controlsignals 128 and receive output signal 130. In some embodiments,processor 106 communicates with transmit module 102 and detect module104 wirelessly. In some further embodiments, processor 106 is integratedin one of transmit module 102 and detect module(s) 104. Note furtherthat in those embodiments including multiple detector modules there maybe multiple output signals 130 communicated with processor. Note furtherthat in those configurations including multiple detectors included aspart of a single detector module, the multiple detectors may provideindividual, multiple signal lines to the processor as well or may belocally processed by detector module thereby providing a single signalto the processor.

In the depicted, illustrative example, system 100 is mounted on eyeglassframes 108, which includes temples 110, lenses 112, and bridge 114.System 100 is shown mounted on frames 108 such that transmit module 102and detect module(s) 104 are on opposite sides of central axis 126 ofeye 120. Specifically, transmit module 102 is mounted on the frames suchthat it can scan input signal 116 over the full extent of scan region122 and detect module(s) 104 is/are mounted on the frames such thatit/they can receive a portion of input signal 116 reflected from scanregion 122 as reflected signal 118. As noted previously, one or moredetect module(s) may include one or more individual detectors which, aswe shall show and describe, advantageously provide enhanced performanceand informational value for systems, methods, and structures accordingto the present disclosure as compared with the prior art.

In particular, the specific location(s) of the one or more detectmodules including one or more individual discrete detectors may beadjustable on the frame structures such that systems, method, andstructures according to the present disclosure may advantageouslyprovide enhanced informational value for a larger portion of thepopulation. We note further that multiple detect modules and or multipledetectors advantageously improve robustness, more accurate eye profiles,geometry determinations, in addition to the improved gaze direction dataalready noted.

FIG. 2A is a schematic diagram depicting an illustrative geometricarrangement for system 100. At this point that it is noted thataccording to one aspect of the present disclosure that there exists aconfiguration of system 100 that gives rise to a unique point on cornea124 that results in a maximum intensity in the reflection of inputsignal 116 (i.e., reflected signal 118) at detector(s) 204 of detectmodule(s) 104, where detector(s) 204 is/are a discrete detector. For thepurposes of this disclosure, including the appended claims, a “discretedetector” is defined as an optoelectronic device having no more thanfour electrically independent detection regions on a single substrate,where each detection region is operative for providing one electricalsignal whose magnitude is based on the intensity of light incident uponthat detection region. Examples of discrete detectors include detectorshaving only one detection region, split detectors having two detectionregions, four-quadrant detectors having four detection regions, andposition-sensitive detectors. The definition of discrete detectorexplicitly excludes individual pixels, or groups of pixels, within arraydevices for collectively providing spatially correlated imageinformation, such as focal-plane arrays, image sensors, and the like.When input signal 116 is aligned with this point, the angular positionsof scanner 202 within transmit module 102 are indicative of the locationof this point of maximum reflection within scan region 122, which isindicative of the corneal vector for the eye.

As may be observed from FIG. 2A, are position(s) of cornea 124 at threegazing positions namely, (1) gazing straight ahead and aligned withcentral axis 126, as indicated by cornea 124′ and corneal vector CV′;(2) gazing in the extreme positive direction, as indicated by cornea124″ and corneal vector CV″; and (3) gazing in the extreme negativedirection, as indicated by cornea 124′″and corneal vector CV′″.

Turning now to FIG. 2B, there is shown a schematic diagram depicting anexemplary scan region 122 of a subject eye. As illustratively depicted,scan region 122 extends from x=xMin to x=xMax and from y=yMin to y=yMaxin the x- and y-directions, respectively.

During an illustrative eye-tracking operation of system 100, scanner 202sweeps input signal 116 over scan region 122 in two dimensions.Preferably, scanner 202 is a two-axis, resonant microelectromechanicalsystem (MEMS) beam scanner, examples of which are described in the '146,'912, and '416 publications; however, other two-dimensional scanners canbe used in system 100 without departing from the scope of the presentdisclosure. When the input signal is incident on cornea 124, reflectedsignal 118 (i.e., the corneal reflection) sweeps over detector 204. Wenote that during operation, the two-dimensional scan may occursimultaneously i.e., it moves in both directions simultaneously and maybe projected onto the eye in a specific pattern to provide enhancedoperation. It should be noted that the curvature of the cornea givesrise to a reflective condition that reduces the angle-of-reflection to anarrow range of scanner angles.

The position of the scanner that corresponds to the maximum receivedintensity at the aperture of detector 204 is then determined based onany of a variety of tracking methodologies described in the '146, '912,and '416 publications, such as tracking maximum intensity, pulse width,pulse leading edge, pulse last edge, and the like. The position of thescanner is then used to calculate the location of the cornea, which isthen used to estimate corneal vector CV.

As previously noted, the particular sweep of input signal mayadvantageously be shaped over scan region(s) such that a desired sweepdensity is achieved thereby producing a desirable (i.e., greatest)density of received pulses produced by the one or more discretedetectors. While the particular sweep shape is user definable, oneparticular shape—the Lissajous—produces a surprisingly effective sweepand therefore pulse densities.

Those skilled in the art will appreciate that a Lissajous curve—alsoknown as a Lissajous figure—is the graph of a system of parametricequations defined by x=A sin(at+δ); y=B sin(bt).

Operationally—with systems, methods and structures according to thepresent disclosure that may advantageously employ MEMS devices, both x,and y axis of the MEMS are driven near their resonant frequencies whichadvantageously results in enhanced power and mechanical range(s). Offurther advantage, a Lissajous curve provides a superior scan patternfor a given surface, as it permits a very fast (in some cases, thefastest) scan speed for a given mechanical system having mechanicalbandwidth constraints.

When scanning to determine glints (eye features), one wants to cover ascan area in a reasonably short period of time such that the feature isalso located within the reasonably short period of time. As will befurther understood and appreciated by those skilled in the art, not allLissajous curves exhibit the same pattern density, which is a functionof the mechanical resonances of the MEMS device employed and the drivefrequencies provide to it.

Still further, as discussed in the '416 publication, a scan region canbe interrogated with greater density in a shorter period of time byscanning a light signal in a Lissajous scan pattern whose position inthe scan region changes over time (i.e., precesses)—preferably at a highrate. Such a scan pattern is generated, for example, by driving eachaxis of scanner 202 with a periodic signal having a frequency near theresonant frequency of that axis and such that two drive frequencies arerelated by a ratio that gives rise to a level of precessing that resultsin a high-density scan pattern in only a few periods of the drivefrequencies.

FIGS. 3A-B shows examples of precessing Lissajous curve patternsgenerated by driving a two-axis, resonant MEMS scanner with drivesignals having different drive-frequency ratios according to aspects ofthe present disclosure.

Plot 300 shows a Lissajous scan overlaying an image of scan region 122,where the scan region includes pupil 302 and iris 304 of eye 120. TheLissajous scan shown in plot 300 is generated using drive signals havinga frequency ratio of 3:5.

Plot 302 shows a Lissajous scan overlaying an image of scan region 122,where the Lissajous scan is generated using drive signals having afrequency ratio of 7:11.

As can be seen from plots 300 and 302, a significant change in the scandensity of a Lissajous scan can be realized by changing the ratio of thefrequencies used to drive its axes. Here, scan density is defined as theinverse of the largest modulo 2π distance, D_(max), among spatiallyadjacent pairs of scan lines in phase space, for a given finite samplingtime.

FIGS. 4 depicts a plot of D_(max) of a scan pattern versus the number ofdrive-signal cycles, k, for two drive signals having different sets ofdrive frequencies.

Plot 400 includes traces 402 and 404, which show the progression of thevalue of D_(max) over successive periods of the lower-frequency drivesignal of the drive-signal pair for drive frequencies having 20:41 and20:43 ratios, respectively.

Each of traces 402 and 404 are characterized by the same baseline valueBV, which is equal to approximately π/16 in the depicted example.However, the conversion time, τ2, for the test-frequency pair having aratio of 20:43 (i.e., trace 404) is significantly shorter than theconversion time, τ1, for the test-frequency pair having a ratio of 20:41(i.e., trace 402). For the purposes of this Specification, including theappended claims, “conversion time” is defined as the time required forthe largest modulo 2π distance of a scan pattern to reach a value thatdiffers from its baseline value by less than a desired offset. In thedepicted example, the desired offset is equal to π/25; however, anyoffset value can be used without departing from the scope of the presentdisclosure.

Specifically, plot 404 shows that the drive-frequency ratio of 20:43approaches baseline value BV in only 14 cycles of its test drivefrequency f_(T) 1, reaching this baseline value in only 28 cycles. Incontrast, the drive-frequency ratio of 20:41 requires 38 cycles of itsf_(T) 1 to approach BV and 39 cycles to reach its base value.Alternatively, in some embodiments, threshold value TV is used as ametric in place of baseline value BV, where TV is a user-defined valuefor any of a wide range of eye-tracker system attributes. This isparticularly advantageous when different drive-frequency ratios arecharacterized by different baseline values. In the depicted example,threshold value TV for a minimum acceptable spatial density foreye-tracking system 100.

As noted above, a Lissajous curve can be described by parametricequations x=A sin(at+δ); y=B sin(bt). It should be noted, however, thatthe drive signals used to realize a Lissajous curve can also include aDC component that can be controlled in accordance with the presentdisclosure. As a result, the teachings herein enable the drive signalsused to drive scanner 202 to be set/adjusted to pan and/or size theresultant scan pattern as desired. For example, during operation, if aparticular glint, or other feature, is detected and subsequentlytracked, scanner 202 can be set/adjusted to target or otherwise “zoomin” on that feature or set of features.

Panning to and/or zooming in on a specific sub-region of the scan regioncan be achieved by adjusting the average power in one or both drivesignals provided to scanner 202 to generate a Lissajous pattern. When aglint is being detected while the pattern is being panned, its timingwill be offset by an amount corresponding to the shift in the pattern.This timing information may be advantageously used to center theprojected pattern around a glint or to position the pattern such that,for example, multiple glints are captured for a given eye (user) with aspecific inter-pupil distance (IPD) and eye relief.

The ability to pan and/or zoom to a specific sub-region within a scanregion affords embodiments in accordance with the present disclosurewith unique and significant advantages over the prior art, such as:

-   -   i. enabling the scan resolution to be set to any desired level;        or    -   ii. enabling the scan resolution to be substantially optimized;        or    -   iii. reduced computation cost for identifying the center of a        glint or eye feature (e.g., pupil, iris, eyelid, etc.); or    -   iv. establishing a “center of mass” for a plurality of        identified glints by, for example, weighting the identified        midpoint of each glint by a feature of its detected pulse (e.g.,        pulse width, leading edge, trailing edge, etc.); or    -   v. any combination of i, ii, iii, and iv.

Furthermore, the ability to pan/zoom on a specific region of scanningregion 122 enables improved resolution in that region. As a result, itcan become possible to identify features that might otherwise bedifficult, if not impossible, to detect, such as the iris of the eye. Asan added benefit, the scan pattern can be centered so that motion ofinput signal 116 is fastest in a region having little or no usefulinformation (e.g., the center of pupil 302) but is slower moving inregions of particular interest (e.g., an iris region).

Similarly, any curve parameterized by two periodic signals withdifferent periods that can be separated into independent axes can berepresented in the same phase space as a Lissajous curve, and canwithstand the same analysis. For example, a Lissajous curve under ageometric coordinate transformation, or a two-axis triangle wave.

It is yet another aspect of the present disclosure that, in addition totracking the gaze direction of an eye, systems, methods, and structuresaccording to aspects of the present disclosure may advantageously detectreflections resulting from other eye features/structures, such as theedge of pupil 302, the sclera, and the like, which can be used togenerate images and/or videos of these features and, in some case, theentire eye and surrounding tissue. Furthermore, other user features andbehavior can be detected/tracked, such as blinks, blink rate, eyeliddroop, eyelid spasms, etc., which can be indicative of a user's physicalor mental condition. For example, such characteristics can indicatefatigue (e.g., while driving, flying, performing surgery, etc.),concussion, inebriation, and the like.

Extraction of eye features from the detector outputs can be performedusing electronic circuits and a comparator circuit or comparatoroperation in software. For systems comprising multiple detectors, theirsignals can be combined via a summing circuit or summing operation insoftware. Preferably, these operations are performed before the signalis converted to a digital signal because analog circuitry can, forexample, be faster, lower cost, consume less power, and/or have smallerphysical size, as compared to a digital signal processor.

As with corneal reflections, such feature/structure reflections may beemployed to determine gaze direction and tracking as well. We note thatsuch feature/structure reflections may be quite subtle, and thereforeany thresholds must be set sufficiently low so that signals associatedwith such features/structures are adequately detected and subsequentlyidentified.

In some embodiments, the detection threshold is set at a level thatenables detection of the interface between pupil 302 and the tissuesurrounding it (i.e., pupillometry). Operationally, systems, methods,and structures according to aspects of the present disclosure determinethe shape of pupil 302 from the timings of detection-threshold crossingsin any (arbitrary) directions.

FIG. 5 depicts operations of a method suitable for identifying athresholded feature according to aspects of the present disclosure. Inthe depicted example, the thresholded feature is the pupil of the eye(i.e., pupil 302); however, any feature having sufficient contrast(e.g., a glint, etc.) can be identified using methods in accordance withthis disclosure. Method 500 begins with operation 501, wherein inputsignal 116 is scanned in a two-dimensional pattern over scan region 122.In the depicted example, input signal 116 is scanned using a Lissajouspattern as described above (e.g., scan pattern 302). In someembodiments, a different periodic two-dimensional scan pattern is usedto steer input signal 116 about scan region 122. Method 500 is describedwith continuing reference to FIGS. 1-3 , as well as reference to FIGS.6A-C.

At operation 502, the intensity of reflected signal 118 is measured byat least one detector of detect module 104 over a test period. In thedepicted example, the test period is equal to one half of one scanperiod of scan pattern 302. In some embodiments, the test period is atime period other than a half of one scan period of the scan pattern. Insome embodiments, the optical intensity received at more than onedetector is measured.

At operation 503, threshold TH1 is established based upon the lowestdetected intensity in output signal 130 over the test period.

FIG. 6A depicts a plot of output signal 130 over the measured half-scanperiod of scan pattern 302. Plot 600 includes trace 602 and thresholdTH1.

Trace 602 represents the intensity of reflected signal 118 versus timefor the test period. Typically, trace 602 represents signal levelscorresponding to specular glints from the cornea, diffuse reflectionsfrom the iris, and reflections from other features of the eye. Because apupil traps nearly all of the light incident upon it, the portion oftrace 602 having the lowest value is typically associated with pupil302. Threshold TH1 is normally established as a level between this valueand an intermediate value, such as might be associated with diffusereflection from the iris.

At operation 504, the optical intensity of reflected signal 118 ismeasured by detector module 104 over a measurement period. In thedepicted example, the measurement period is equal to four full scanperiods of scan pattern 302; however, any suitable value can be selectedfor the measurement period. Typically, the measurement period isselected as a plurality of whole or fractional scan periods of scanpattern 302 that is large enough to provide confidence in the detectedfeatures but small enough to mitigate the chance that eye 120 will moveduring the measurement period. The measured optical intensity ofreflected signal 118 is provided to processor 106 as output signal 130.

In some embodiments, a value for TH1 is established prior toimplementing method 500. In such embodiments, operations 501 through 503are not necessary and method 500 begins with operation 504.

At operation 505, comparator 132 provides comparator signal 134 based ona comparison of the magnitude of output signal 130 to threshold TH overthe measurement period. In the depicted example, comparator signal 134is high when the magnitude of output signal 130 is less than thresholdTH and low when the magnitude of output signal 130 is equal to orgreater than threshold TH. In the depicted example, comparator 132 isincluded in processor 106; however, the comparator can be locatedelsewhere in system 100, such in detect module 104, etc.

At optional operation 506, a two-dimensional map of the comparatorsignal 134 over the measurement period is generated.

FIG. 6B depicts a two-dimensional map of comparator signal 134. Plot 604is based on a spatiotemporal correlation between comparator signal 134and the position of scanner 202 over the measurement period, which givesrise to a 1-bit image of the eye (i.e., a single-level contour plot)having only dark and light regions.

At operation 507, contour plot (CP) 608 is generated the position of itscenter in x,y space is extracted from plot 604. In the depicted example,CP 608 is representative of the perimeter of pupil 302.

In some embodiments, plot 604 is not generated and CP 608 is estimatedbased a correlation of timing information in comparator signal 134(e.g., the times of the leading and trailing edges of its output) andthe corresponding positions of MEMS scanner 202.

FIG. 6C depicts a reconstructed pupil signal in accordance with method500. Plot 606 shows the outline of pupil 302 (i.e., CP 608) andcalculated centroid (x1,y1) of CP 608.

At this point we note that when attempting pupillometry, the signals arenot necessarily low as they are determined by the contrast from pupil toiris. The contrast is actually quite high—although orders of magnitudeless than a glint. One significant problem with pupillometry, however,is that of non-uniform illumination/sensitivity across a scan range. Inother words, pupillometry is negatively impacted by the non-uniformillumination wherein the path length between scanner and detector variesacross the scan range as reflected from the features of the eye. Anincreased path length drops the detected signal and therefore createsgradients that makes fixed threshold pupil detection difficult.

Advantageously, and according to still further aspects of the presentdisclosure, one way to overcome this infirmity is to sum the signalsfrom multiple photodetectors such that the average path length of thebeam(s) is roughly equal as compared with any signal drop magnitudecreated by the pupil. Such summing may also be performed in a weightedmatter such that the signal is “leveled” against the background. Thiscalibration may occur—for example—when a user has their eyes closed soas to optimize a uniform diffuse reflection signal in the absence of thepupil thus making pupil detection easier.

For example, multiple input signals may be received at the same eye (orother object of interest), where each input signal arrives from adifferent transmit module at a different orientation, such that multipleunique perspectives of the eye are achieved. The information from theperspective of one input signal may be selected to be used by thesoftware over the other input signals. For example, the eye may belooking toward one transmit module, thereby providing that transmitmodule the best quality of data to be processed by the circuits and thesoftware. One detector may also be shared by multiple scanners by forexample, orthogonally modulating light in time-domain such that thesignal source can be determined.

Each eye scanner may have properties that are different than the othereye scanners, including but not limited to their operationalwavelengths, scanning speed or frequency, modulation data, modulationfrequency, detector gain, optical power, field of view, polarization,and size. The use of different properties may allow for each eye scannerto operate simultaneously without interfering with the others. The useof different properties may allow for unique interactions with theobject of interest, such as wavelength absorption, reflectance of thewhole or parts of the object of interest, polarizing regions of theobject of interest, and more.

Still further, closed-loop control can be implemented to addressnon-uniformities associated with illumination and/or MEMS scannerperformance. Scanner properties that can be controlled in closed-loopfashion include, without limitation, optical power, scan angles, andscan speed, including reducing any property to zero (off). Detectorproperties that can be controlled in closed-loop fashion include,without limitation, gain, threshold, bandwidth, and modulationfrequency, including reducing any property to zero (off). Furthermore,in some embodiments, the intensity of the light emitted at transmitmodule 102 is monitored to enable closed-loop control of the intensityof input signal 116.

It should be noted that, although closed-loop control offers advantagesin many cases, open loop control can be used without departing from thescope of the present disclosure.

In some embodiments, improved SNR is achieved by periodically turningthe light source in transmit module 102 on/off at a high frequency(i.e., a modulation frequency). In such embodiments, detect module 104includes a detector circuit (e.g., a phase-locked loop, etc.) that istuned to the modulation frequency of the source, thereby enabling it topick up the desired signal while rejecting interfering signals.

It is yet another aspect of the present disclosure that the concept ofpupillometry can be extended to generate a multi-bit image of an eye byemploying a plurality of threshold values against which reflections fromthe eye are compared. As a result, the teachings of the presentdisclosure enable generation of a reflected-intensity map thatrepresents an image of an eye without the need for an expensiveconventional imaging system, such as a camera or focal-plane array.

FIG. 7 depicts operations of a method suitable for forming a multi-levelreflected-intensity map of an eye in accordance with the presentdisclosure. Method 700 is substantially an extension of method 500 andbegins with operation 701, wherein input signal 116 is scanned in atwo-dimensional pattern over scan region 122. In the depicted example,input signal 116 is scanned in a Lissajous pattern over the scan region.Method 700 is described with continuing reference to FIGS. 1-3 , as wellas reference to FIGS. 8A-C.

At operation 702, the intensity of reflected signal 118 is measured byat least one detector of detect module 104 during at least a half of thescan pattern of input signal 116. In some embodiments, the opticalintensity received at more than one detector is measured. In someembodiments, the optical intensity is determined for more than one halfof a scan pattern in operation 702.

For each of j=1 through M, where M is based on the desired dynamic rangein the resultant image:

-   -   i. At operation 703, threshold TH-j is established for        comparator 132. Typically, threshold TH-1 is based upon the        lowest intensity determined in operation 1102.    -   ii. At operation 704, the optical intensity of reflected signal        118 is measured at detector module 104 over a measurement period        to give rise to output signal 130. In the depicted example, the        measurement period is selected as four full cycles of scan        pattern 302.    -   iii. At operation 705, output signal 130 is compared to        threshold TH-j over the measurement period.    -   iv. At operation 706, contour plot CP-j is generated based on        the comparison made in operation 705.

If j<M, the value of j is increased by 1 and method 700 returns tooperation 703, where a new threshold TH-j is established.

FIG. 8A depicts a series of contour plots in accordance with the presentdisclosure. Plot 800 depicts contour plots CP-1 through CP-M, which aregenerated using different threshold values at comparator 132.

After M iterations of operations 703 through 706, method 700 continueswith operation 707 wherein contour plots CP-1 through CP-M are combinedinto composite contour map (CM) 802, which depicts outlines of regionshaving substantially the same reflected intensity.

FIG. 8B depicts a contour map in accordance with the present disclosure.Contour map 802 comprises contour plots CP-1 through CP-M.

At operation 707, software interpolation is used to generate multi-levelreflected-intensity map 804 from CM 802. In some embodiments, thesoftware interpolation is a simple linearization of reflected-intensityvalues between contours.

FIG. 8C depicts an image of an eye derived by interpolating a contourmap in accordance with the present disclosure. It should be noted thatthe image is a multi-level reflected-intensity map 804 of eye 120.

FIG. 9 depicts image plots of a portion of a face, based on multi-levelreflected-intensity plots reconstructed using different numbers of bitsof information in accordance with the present disclosure.

Object 900 is a portion of the face of a user, which includes one of theuser's eyes, with a high number of bits of information.

Image 902 is an image of object 900 reconstructed via method 700, whereM=2 (i.e., with two bits of information).

Image 904 is an image of object 900 reconstructed via method 700, whereM=3 (i.e., with three bits of information).

It should be noted that imaging approaches in accordance with thepresent disclosure are not limited to eye scanning and can be used tocapture contour maps of a wide range of objects of interest, such asfacial features, inanimate objects, and the like.

In some embodiments, some or all of the operations of method 700 aresequentially repeated over a period of time to generate a contour-mapvideo of scan region 122.

In some embodiments, a contour map is generated by varying a differentsystem parameter (e.g., the intensity of input signal 116 and/or thegain of the detector(s) of detect module 104) while keeping thethreshold employed by comparator 132 fixed. in some embodiments, thethreshold remains fixed while is varied in operation 703. Furthermore,in some embodiments the variation applied to the threshold/systemparameter is varied according to a periodic function, thereby obtainingcontinuous multi-bit information about the scan region.

Although system 100, as described herein, includes a single transmitmodule that provides only one input signal, in some embodiments,multiple MEMS scanners, each providing a different input signal are usedwith multiple detectors to augment the capabilities of an eye-trackingsystem. For example, three-dimensional sensing is enabled by the use oftwo or more input signals in conjunction with a plurality of detectors.Preferably, the scanners that provide the input signals are positionedsuch that they are apart at a reasonably high angle, which enables animage or video obtained at each scanner's perspective can be correlatedthrough software techniques to determine the 3D location of an object ofinterest and/or its features (e.g., an eye and its iris, pupil, cornea,lid, etc.). This correlation may easily be determined on the pupil andthe cornea, because the pupil is typically the darkest feature in theimage, while the corneal glint(s) are often the brightest. Thus, theminimum and maximum intensity locations in each image serve as pointsfor correlation. The 3D location information is useful for quick andlightweight calculation of the location and orientation of the eye (thegaze angle in particular).

It is yet another aspect of the present disclosure that a single-bitquantizer can be used to generate a multibit reflected-intensity map byperforming a successive approximation method to determine the value ofeach “pixel” in the image (i.e., each location of the scan pattern inscan space whose value is to be determined.

In one nonlimiting exemplary approach, the successive approximationmethod is successive approximately ADC method comprising a binary searchthat is initialized by starting with an image table populated with amid-scale value (128, for example, in an 8-bit unsigned scale) for eachpixel. As the beam traverses scan region 122 in a Lissajous pattern, ateach pixel, a digitized value of the intensity of input signal 116 iscompared to its current magnitude in the image table .

If the result of the comparison is high, a binary step up is taken forthat pixel value in the image table. As the beam traverses scan region122, each pixel is interrogated once per scan and is not re-interrogateduntil the Lissajous pattern returns to its location.

For example, the magnitude of a given pixel with an unsigned 8-bit valueof 177 would proceed through the following sequence of interrogations:128, 192, 176, 184, 180, 178, 177. An error of up to 1 least-significantbit (LSB) is expected and so extra single stepping may be added forinterpolation or averaging depending on the SNR of the pixel ordrive/sense system.

Each pixel is interrogated once per Lissajous frame and requires only Ninterrogations per bits of depth. The sampling period of the ADC must beat least as fast as the traversal time of the beam across a pixel siteand the resolution of the DAC setting the intensity of the input signal116 should at least equal the bit depth of the target image.

In some embodiments, a different successive approximation method, suchas counter-type ADC, servo-tracking ADC, and the like, is used.

While any suitable approach to image reconstruction can be used withoutdeparting from the scope of the present disclosure, there are someimage-construction approaches that offer particular advantages over theprior art. Such advantages arise, in part, from the fact that:

-   -   i. MEMS scanner 202 is driven by a periodic signal; therefore,        it produces a periodic response having phase values that        correspond to the physical configuration of the MEMS scanner;    -   ii. Each axis of the MEMS scanner will have a corresponding        phase;    -   iii. A scanner with N scan axes will scan a M-dimensional        physical configuration in space (where M≤N and typically M=N);    -   iv. an analog signal in time can be sampled as the scanner is        scanned; and    -   v. each sample in time corresponds to a position in phase.

Based on the above, examples of preferable image-reconstruction approachcan be described as:

Reconstruction:

-   -   i. construct an N-dimensional accumulator array, with entries        corresponding to discretized coordinates in phase space;    -   ii. map a given signal sample to its position in phase space,        which is then accumulated into the accumulator array;    -   iii. gather the phase accumulator into a scan-space        M-dimensional array (M≤N), representing discretized coordinates        in a space which is bijective with the physical configuration of        the scanner (e.g., mirror angle space, image space,        distortion-corrected image space, etc.); and    -   iv. directly scatter the time-domain signal into the scan space        (if the transformation from the phase accumulator to the scan        space is adequately simple to compute); OR scatter the        time-domain signal into phase space and subsequently gather it        into scan space in post-processing. It should be noted that the        transformation from phase space to scan space can be encoded in        a look up table.

Accumulation:

-   -   i. finding the nearest bin and scatter of the time domain signal        into the accumulator (whether in phase or scan space);

OR

-   -   ii. replace accumulating with one or more of cumulative        averaging, windowed averaging, computation of variance or other        measure of spread, or use a kernel (e.g., an anti-aliasing        kernel) for accumulating in nearby bins to reduce quantization        error.

Sampling:

-   -   i. sample at regular time intervals, which correspond to regular        increments in phase space;    -   ii. derive an alternative scatter space, where the scatter space        is a linear transformation of the phase space such that the        scatter space is cache coherent;    -   iii. gather the alternative scatter space into phase space or        directly into scan space;    -   iv. invert the nonlinearity of the transformation from phase        space to scan space and apply it to modulate the sampling rate        to produce samples which are spaced regularly in the scan space;    -   v. up-modulate the sampling rate (if there is a salient point in        the scan space) to produce denser data in the scan space where        it is desired (e.g., an iris);    -   vi. If it's not possible to sample at an adequate rate during a        given scan period, the sampling rate can set such that        subsequent scan passes produce measurements slightly offset in        space, to fill in the holes. Note that this is similar to the        effect of setting scan frequencies to produce precessing scans        that cover more scan positions over time

It is to be understood that the disclosure teaches just some examples ofillustrative embodiments and that many variations of the invention caneasily be devised by those skilled in the art after reading thisdisclosure and that the scope of the present invention is to bedetermined by the following claims.

What is claimed is:
 1. An apparatus comprising: a firstmicroelectromechanical system (MEMS) scanner for steering a first inputlight signal in a two-dimensional pattern over a scan region, whereinthe first MEMS scanner has a first scanning axis characterized by afirst resonant frequency and a second scanning axis characterized by asecond resonant frequency; a detector configuration that is non-imagingand includes at least one discrete detector, wherein the detectorconfiguration is configured to provide a first detector signal based afirst reflected light signal from the scan region, the first reflectedlight signal comprising at least a portion of the input light signal; acomparator configured to provide a first comparator signal based on afirst comparison of the first detector signal and a first threshold; anda processor configured to estimate the position of the MEMS scanner andgenerate a first contour plot based on a spatiotemporal correlation ofthe first comparator signal and the estimated position of the MEMSscanner over the first time period.
 2. The apparatus of claim 1 whereinthe processor is further configured to estimate at least one of the sizeand location of a first feature in the scan region based on the firstcontour plot.
 3. The apparatus of claim 1 wherein the scan pattern is aLissajous pattern.
 4. The apparatus of claim 3 wherein the processor isfurther configured to drive the first scanning axis with a firstperiodic signal having a first drive frequency and the second scanningaxis with a second periodic signal having a second drive frequency, andwherein the first and second drive frequencies give rise to a precessionof the Lissajous pattern.
 5. The apparatus of claim 1 wherein theprocessor comprises the comparator.
 6. The apparatus of claim 1 whereinthe first detector signal comprises a combination of a plurality ofsecond detector signals, each of the plurality of second detectorsignals being based on a different reflected light signal of a pluralityof reflected light signals that includes the first reflected lightsignal.
 7. The apparatus of claim 1 wherein the first input light signalis modulated at a modulation frequency, and wherein the detectorconfiguration includes a detector circuit that is tunable to themodulation frequency.
 8. The apparatus of claim 1 further comprising aplurality of MEMS scanners for steering a plurality of input lightsignals, the plurality of MEMS scanners including the first MEMS scannerand the plurality of input light signals including the first input lightsignal, wherein each of the plurality of light signals is directed atthe scan region from a different position and a different orientationwith respect to the scan region.
 9. The apparatus of claim 1 wherein theprocessor is further configured to generate a plurality of contour plotsthat includes the first contour plot, wherein each of the plurality ofcontour plots is based on a spatiotemporal correlation of a differentcomparator signal of a plurality of comparator signals that includes thefirst comparator signal, and wherein each of the plurality of comparatorsignals is based on a comparison selected from the group consisting of:(i) a comparison of the first detector signal and a different thresholdof a plurality of thresholds that includes the first threshold; (ii) acomparison of a plurality of detector signals and the first threshold,wherein the plurality of detector signals includes the first detectorsignal and each of the plurality of detector signals corresponds to adifferent gain for the at least one discrete detector; and (iii) acomparison of a plurality of detector signals and the first threshold,wherein the plurality of detector signals includes the first detectorsignal and each of the plurality of detector signals corresponds to adifferent intensity of the input light signal.
 10. The apparatus ofclaim 9 wherein the processor is further configured to form areflected-intensity map based on the plurality of contour plots.
 11. Amethod comprising: scanning a first input light signal in atwo-dimensional scan pattern over a scan region through the effect of amicroelectromechanical system (MEMS) scanner that has a first scanningaxis characterized by a first resonant frequency and a second scanningaxis characterized by a second resonant frequency, wherein the lightsignal is scanned by driving the first axis with a first periodic signalhaving a first drive frequency and driving the second axis with a secondperiodic signal having a second drive frequency; providing a firstdetector signal based on reflected light from the scan region at adetector configuration that is non-imaging and includes at least onediscrete detector, wherein the reflected light comprises at least aportion of the input light signal; generating a first comparator signalbased on a first comparison of the first detector signal and a firstthreshold; and generating a first contour plot based on a spatiotemporalcorrelation between the first comparator signal and an estimate of theposition of the MEMS scanner over a first time period.
 12. The methodfor claim 11 further comprising estimating at least one of the size andlocation of a first feature in the scan region based on the firstcontour plot.
 13. The method for claim 11 wherein the two-dimensionalscan pattern is a Lissajous pattern.
 14. The method for claim 13 furthercomprising selecting at least one of the first drive frequency andsecond drive frequency to give rise to a precession of the Lissajouspattern.
 15. The method for claim 11 further comprising: modulating thefirst input light signal at a modulation frequency; and configuring adetector circuit to detect the modulation frequency.
 16. The method forclaim 11 further comprising: generating a plurality of comparatorsignals that includes the first comparator signal, wherein eachcomparator signal of the plurality thereof is based on a comparison ofthe first detector signal and a different threshold of a plurality ofthresholds that includes the first threshold; and generating a pluralityof contour plots that includes the first contour plot, wherein eachcontour plot of the plurality thereof is based on a spatiotemporalcorrelation between a different comparator signal of the pluralitythereof and an estimate of the position of the MEMS scanner over a firsttime period.
 17. The method for claim 11 further comprising: generatinga plurality of comparator signals that includes the first comparatorsignal, wherein each comparator signal of the plurality thereof is basedon a comparison of the first threshold and a different detection signalof a plurality of detector signals that includes the first detectorsignal, wherein each of the plurality of detector signals is generatedusing a different gain for the at least one discrete detector; andgenerating a plurality of contour plots that includes the first contourplot, wherein each contour plot of the plurality thereof is based on aspatiotemporal correlation between a different comparator signal of theplurality thereof and an estimate of the position of the MEMS scannerover a first time period.
 18. The method for claim 11 furthercomprising: generating a plurality of comparator signals that includesthe first comparator signal, wherein each comparator signal of theplurality thereof is based on a comparison of the first threshold and adifferent detection signal of a plurality of detector signals thatincludes the first detector signal, wherein each of the plurality ofdetector signals corresponds to a different intensity of the first inputlight signal; and generating a plurality of contour plots that includesthe first contour plot, wherein each contour plot of the pluralitythereof is based on a spatiotemporal correlation between a differentcomparator signal of the plurality thereof and an estimate of theposition of the MEMS scanner over a first time period.
 19. The methodfor claim 11 further comprising generating a multibitreflected-intensity map of the scan region using a successiveapproximation method selected from the group consisting ofsuccessive-approximation analog-to-digital conversion (ADC),counter-type ADC, and servo-tracking ADC.
 20. The method for claim 19wherein the successive approximation method is successive-approximationADC based on a binary search.